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Data structure for representing information using expressions

a data structure and expression technology, applied in relational databases, database models, instruments, etc., can solve problems such as burden on computer users, administrators or application program developers, and inability to add a new structure to a defined data structure, and achieve the effect of reducing the burden on computer users and administrators or application program developers, and reducing the flexibility of data structures proposed conventionally

Active Publication Date: 2018-06-05
MAEDA CORPORATION
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

Enables efficient division and restoration of information, reducing processing time and administrative burdens by allowing flexible handling of new attributes and hierarchical structures.

Problems solved by technology

However, databases proposed conventionally have a problem in terms of flexibility toward changes, being unable to add a new structure to a defined data structure.
For example, when a new attribute is added to one table after a relational database goes into operation, it is necessary to modify an existing data structure and an application program that processes the data structure, and man-hours needed for the modification are burdens on computer users and administrators or application program developers.
Also, with conventional relational databases, it is not possible to hierarchically describe information, i.e., for example, define a table further in an attribute of a table.

Method used

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  • Data structure for representing information using expressions
  • Data structure for representing information using expressions
  • Data structure for representing information using expressions

Examples

Experimental program
Comparison scheme
Effect test

examples

[0068]

T×(ABC×(ab1+ac2+bc3)+A×(ab1+ac2)+B×(ab1+bc3)+C(ac2+bc3)),

fruits×(all types×(apple+banana+mandarin orange)+red×apple+yellow×(banana+mandarin oranges)), fruits×(all types×(apple+banana+mandarin orange)+round×(apple+mandarin orange)+elongated×banana),

vegetables×(all types×(Japanese radish+cucumber+burdock)+thick×Japanese radish+thin×(cucumber+burdock)), company×(employee×(employee 1+employee 2+employee 3+employee 4)+business×(employee 1+employee 2)+accounting×(employee 3+company 4)),

[0069]In this case, the last (fifth) example is updated as follows, if, for example, a general affairs department is newly established and employee 5 is adopted and assigned to the general affairs department.

EXAMPLE

[0070]

company×(employee×(employee 1+employee 2+employee 3+employee 4+employee 5)+business×(employee 1+employee 2)+accounting×(employee 3+employee 4)+general affairs department×employee 5)

(5) Adjunction Space Information

[0071]Adjunction space information is made up by relating subsets includ...

division example 1

[0150]

(Germany (expression 1)+France (expression 2)),

(Japan (expression 3)+Germany (expression 4)+France (expression 5)+Japan (expression 6)+Germany (expression 7)+France (expression 8)+Japan (expression 9)+ . . . )

[0151]Also, the dividing position may be determined based on data size such that the subsets resulting from the division will be within a predetermined size. In this case, an amount of data is calculated, for example, beginning with the top of data and the target information is divided at a position between terms existing just before a predetermined threshold is exceeded. This makes it possible to divide the target information such that the sizes of the expressions resulting from the division will be equal to or smaller than a fixed value. For example, if a predetermined size is exceeded between the top and the middle of expression 5 and the predetermined size is exceeded between the end of expression 4 and the middle of expression 9, the target information is divided int...

division example 2

[0152]

(Germany (expression 1)+France (expression 2)+Japan (expression 3)+Germany (expression 4)),

(France (expression 5)+Japan (expression 6)+Germany (expression 7)+France (expression 8)),

(Japan (expression 9)+ . . . )

[0153]Also, the target information may be divided into subsets of terms such that the terms in each subset will have in common a predetermined factor connected by the product operator. This makes it possible to divide the target information according to meanings and features of information. Referring to the above-mentioned example of the expression-based representation, factors such as “Germany,”“France,” and “Japan,” which are country names, are joined to other factors by the product operator in respective terms. Thus, if terms having in common, for example, a factor connected to the left by the product operator in each term are grouped into a subset, the target information is divided into three subsets as follows.

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PUM

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Abstract

An information processing device processes target information described using identifiers formed from a symbol, a product operator that joins together factors containing one or more of the identifiers and thereby forms a string of ordered factors, and a sum operator that joins together terms containing one or more of the factors and thereby forms an expression that is a combination of the terms. Also, information processing device includes a dividing unit that divides the target information into a plurality of terms at a predetermined position; and a transmission unit that associates positional information with at least any of the factors contained in the terms resulting from the division and causes each of the terms resulting from the division to be held in any of a plurality of server devices, where the positional information contains an occurrence sequence of the terms in the target information and an occurrence sequence of the factors in the terms.

Description

TECHNICAL FIELD[0001]The present invention relates to an information processing device, an information processing method, and a program.BACKGROUND ART[0002]Conventionally known data structures handled by computers include, for example, tabular structures of relational databases, objects of object-oriented databases, and frames or rules of knowledge databases.[0003]However, databases proposed conventionally have a problem in terms of flexibility toward changes, being unable to add a new structure to a defined data structure. For example, when a new attribute is added to one table after a relational database goes into operation, it is necessary to modify an existing data structure and an application program that processes the data structure, and man-hours needed for the modification are burdens on computer users and administrators or application program developers. Also, with conventional relational databases, it is not possible to hierarchically describe information, i.e., for exampl...

Claims

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Application Information

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Patent Type & Authority Patents(United States)
IPC IPC(8): G06F17/30
CPCG06F17/30604G06F17/30498G06F17/30339G06F17/30312G06F17/30587G06F16/28G06F16/288G06F16/22G06F16/2282G06F16/2456
Inventor SEKI, YOICHIKUNII, TOSIYASUKODAMA, TOSHIOMOMOSE, KIMIO
Owner MAEDA CORPORATION
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